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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 11, issue 5 | Copyright
Atmos. Meas. Tech., 11, 2653-2668, 2018
https://doi.org/10.5194/amt-11-2653-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 07 May 2018

Research article | 07 May 2018

How well can global chemistry models calculate the reactivity of short-lived greenhouse gases in the remote troposphere, knowing the chemical composition

Michael J. Prather1, Clare M. Flynn1, Xin Zhu1, Stephen D. Steenrod2,3, Sarah A. Strode2,3, Arlene M. Fiore4, Gustavo Correa4, Lee T. Murray5, and Jean-Francois Lamarque6 Michael J. Prather et al.
  • 1Department of Earth System Science, University of California, Irvine, CA 92697-3100, USA
  • 2NASA Goddard Space Flight Center, Greenbelt, MD, USA
  • 3Universities Space Research Association (USRA), GESTAR, Columbia, MD, USA
  • 4Department of Earth and Environmental Sciences and Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, USA
  • 5Department of Earth and Environmental Sciences, University of Rochester, Rochester, NY 14627-0221, USA
  • 6Atmospheric Chemistry, Observations and Modeling Laboratory, National Center for Atmospheric Research, Boulder, CO 80301, USA

Abstract. We develop a new protocol for merging in situ measurements with 3-D model simulations of atmospheric chemistry with the goal of integrating these data to identify the most reactive air parcels in terms of tropospheric production and loss of the greenhouse gases ozone and methane. Presupposing that we can accurately measure atmospheric composition, we examine whether models constrained by such measurements agree on the chemical budgets for ozone and methane. In applying our technique to a synthetic data stream of 14880 parcels along 180°W, we are able to isolate the performance of the photochemical modules operating within their global chemistry-climate and chemistry-transport models, removing the effects of modules controlling tracer transport, emissions, and scavenging. Differences in reactivity across models are driven only by the chemical mechanism and the diurnal cycle of photolysis rates, which are driven in turn by temperature, water vapor, solar zenith angle, clouds, and possibly aerosols and overhead ozone, which are calculated in each model. We evaluate six global models and identify their differences and similarities in simulating the chemistry through a range of innovative diagnostics. All models agree that the more highly reactive parcels dominate the chemistry (e.g., the hottest 10% of parcels control 25–30% of the total reactivities), but do not fully agree on which parcels comprise the top 10%. Distinct differences in specific features occur, including the spatial regions of maximum ozone production and methane loss, as well as in the relationship between photolysis and these reactivities. Unique, possibly aberrant, features are identified for each model, providing a benchmark for photochemical module development. Among the six models tested here, three are almost indistinguishable based on the inherent variability caused by clouds, and thus we identify four, effectively distinct, chemical models. Based on this work, we suggest that water vapor differences in model simulations of past and future atmospheres may be a cause of the different evolution of tropospheric O3 and CH4, and lead to different chemistry-climate feedbacks across the models.

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A new protocol for merging in situ atmospheric chemistry measurements with 3-D models is developed. This technique can identify the most reactive air parcels in terms of tropospheric production/loss of O3 & CH4. This approach highlights differences in 6 global chemistry models even with composition specified. Thus in situ measurements from, e.g., NASA's ATom mission can be used to develop a chemical climatology of, not only the key species, but also the rates of key reactions in each air parcel.
A new protocol for merging in situ atmospheric chemistry measurements with 3-D models is...
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